Characterizing an indoor structure based on detected movements and/or position locations of a mobile device

ABSTRACT

Various methods, apparatuses and articles of manufacture are provided which may be implemented in various devices for use in characterizing a signaling environment in an area of location uncertainty within an indoor structure. In an example, a computing device may obtain at least a portion of a travel log indicative measurements gathered by a mobile device within an area of location uncertainty, and a position fix based, at least in part, on one or more signals received at the mobile device within an area of location certainty. The computing device may, for example, determine an estimated trajectory of the mobile device within at least a portion of the area of location uncertainty within an indoor structure, e.g., leading to the position fix, based, at least in part on at least a portion of the plurality of measurements and the position fix.

CROSS-REFERENCE TO RELATION APPLICATIONS

This patent application is a divisional of U.S. patent application Ser.No. 13/297,733, entitled, “CHARACTERIZING AN INDOOR STRUCTURE BASED ONDETECTED MOVEMENTS AND/OR POSITION LOCATIONS OF A MOBILE DEVICE”, filedNov. 16, 2011, which is assigned to the assignee hereof and which isincorporated herein by reference.

BACKGROUND

1. Field

The subject matter disclosed herein relates to electronic devices, andmore particularly to methods, apparatuses and articles of manufacturefor use in characterizing an area of location uncertainty within anindoor structure based on detected movements and/or position locationsof a mobile device.

2. Information

The Global Positioning System (GPS) represents one type of GlobalNavigation Satellite System (GNSS), which along with other types ofsatellite positioning systems (SPS) provide or otherwise supportsignal-based position location capabilities (e.g., navigation functions)in mobile devices, and particularly in outdoor environments. However,since some satellite signals may not be reliably received and/oracquired by a mobile device within an indoor environment, differenttechniques may be employed to enable position location services.

For example, mobile devices may attempt to obtain a position fix bymeasuring ranges to three or more terrestrial transmitters (e.g.,wireless access point devices, beacons, cell towers, etc.) which arepositioned at known locations. Such ranges may be measured, for example,by obtaining a MAC ID address from signals received from suchtransmitters and obtaining range measurements to the transmitters bymeasuring one or more characteristics of signals received from suchtransmitters such as, for example, signal strength, a round trip timedelay, etc.

These and other like position location and navigation techniques tend tobe of further benefit to a user if presented with certain mappedfeatures. For example, mapped features may relate to or otherwiseidentify certain physical objects, characteristics, or points ofinterest within a building or complex, etc. Thus, in certain instances,an indoor navigation system may provide a digital electronic map to amobile device upon entering a particular indoor area, e.g., in responseto a request for position assistance data. Such a map may show indoorfeatures such as doors, hallways, entry ways, walls, etc., points ofinterest such as bathrooms, pay phones, room names, stores, etc. Such adigital electronic map may be stored at a server to be accessible by amobile device through selection of a URL, for example. By obtaining anddisplaying such a map, a mobile device may overlay a current location ofthe mobile device (and user) over the displayed map to provide the userwith additional context.

In certain instances, some of the information that may be provided toand/or otherwise used by a mobile device for navigational or other likepurposes may change from time to time, or may even be unknown. Thus, itmay be useful to determine whether such information may have changed, orto otherwise gather and/or develop such information in an efficientmanner.

SUMMARY

In accordance with an example aspect, a method at a computing device maycomprise: obtaining one or more signals representing at least a portionof a travel log from a mobile device, said travel log being indicativeof or based at least in part on: a plurality of measurements gathered bysaid mobile device during a period of time within an area of locationuncertainty, and a position fix at or subsequent to an end of saidperiod of time based, at least in part, on one or more signals receivedat said mobile device within an area of location certainty; anddetermining an estimated trajectory of said mobile device within atleast a portion of said area of location uncertainty within an indoorstructure leading to said position fix based, at least in part on atleast a portion of said plurality of measurements and said position fix.

In accordance with another example aspect, an apparatus for use in acomputing device may comprise: means for obtaining at least a portion ofa travel log from a mobile device, said travel log being indicative ofor based at least in part on: a plurality of measurements gathered bysaid mobile device during a period of time within an area of locationuncertainty, and a position fix at or subsequent to an end of saidperiod of time based, at least in part, on one or more signals receivedat said mobile device within an area of location certainty; and meansfor determining an estimated trajectory of said mobile device within atleast a portion of said area of location uncertainty within an indoorstructure leading to said position fix based, at least in part on atleast a portion of said plurality of measurements and said position fix.

In accordance with yet another example aspect, a computing device maycomprise a network interface, and a processing unit to: obtain, via saidnetwork interface, at least a portion of a travel log from a mobiledevice, said travel log being indicative of or based at least in parton: a plurality of measurements gathered by said mobile device during aperiod of time within an area of location uncertainty, and a positionfix at or subsequent to an end of said period of time based, at least inpart, on one or more signals received at said mobile device within anarea of location certainty; and determine an estimated trajectory ofsaid mobile device within at least a portion of said area of locationuncertainty within an indoor structure leading to said position fixbased, at least in part on at least a portion of said plurality ofmeasurements and said position fix.

In accordance with still another example aspect, an article ofmanufacture may comprise a non-transitory computer readable mediumhaving stored therein computer implementable instructions that areexecutable by a processing unit in a computing device to: obtain atleast a portion of a travel log from a mobile device, said travel logbeing indicative of or based at least in part on: a plurality ofmeasurements gathered by said mobile device during a period of timewithin an area of location uncertainty, and a position fix at orsubsequent to an end of said period of time based, at least in part, onone or more signals received at said mobile device within an area oflocation certainty; and determine an estimated trajectory of said mobiledevice within at least a portion of said area of location uncertaintywithin an indoor structure leading to said position fix based, at leastin part on at least a portion of said plurality of measurements and saidposition fix.

BRIEF DESCRIPTION OF DRAWINGS

Non-limiting and non-exhaustive aspects are described with reference tothe following figures, wherein like reference numerals refer to likeparts throughout the various figures unless otherwise specified.

FIG. 1 is a schematic block diagram illustrating an example environmentthat includes a mobile device and a computing device for use incharacterizing at least a portion of an area of location uncertaintywithin an indoor structure based on detected movements and/or positionlocations of the mobile device, in accordance with an implementation.

FIG. 2 is a schematic block diagram illustrating certain features of anexample mobile device for use in characterizing at least a portion of anarea of location uncertainty within an indoor structure based ondetected movements and/or position locations of the mobile device, inaccordance with an implementation.

FIG. 3 is a schematic block diagram illustrating certain features of anexample computing platform for use at a computing device to characterizeat least a portion of an area of location uncertainty within an indoorstructure based on detected movements and/or position locations of oneor more mobile devices, in accordance with an implementation.

FIG. 4 is a flow diagram illustrating certain features of an exampleprocess or method for a mobile device for use in characterizing at leasta portion of an area of location uncertainty within an indoor structurebased on detected movements and/or position locations of the mobiledevice, in accordance with an implementation.

FIG. 5 is a flow diagram illustrating certain features of an exampleprocess or method for a computing platform for use at an externalcomputing device to characterize at least a portion of an area oflocation uncertainty within an indoor structure based on detectedmovements and/or position locations of one or more mobile devices, inaccordance with an implementation.

FIG. 6 is a diagram illustrating certain detected movements and/orposition locations of a mobile device through at least a portion of anarea of location uncertainty leading to a position fix obtained withinan area of location certainty, in accordance with an implementation.

FIG. 7 is a diagram illustrating that certain detected movements and/orposition locations of a mobile device through at least a portion of anarea of location uncertainty leading to a position fix obtained withinan area of location certainty as in FIG. 6 may be used to estimate atrajectory of movements within an area of location uncertainty an indoorstructure, in accordance with an implementation.

FIG. 8 is a diagram illustrating that certain trajectory of movementswithin at least a portion of an area of location uncertainty within anindoor structure as in FIG. 7 may be used to estimate a path of travelwithin an indoor structure, in accordance with an implementation.

DETAILED DESCRIPTION

As described in greater detail herein, various methods, apparatuses andarticles of manufacture are provided which may be implemented in variousdevices for use in characterizing at least a portion of an area oflocation uncertainty of an indoor structure based on detected movementsand/or position locations of the mobile device.

As used herein, an “area of location uncertainty” is intended to specifyat least one region in space for which wireless signaling locationinformation may be sufficiently lacking (e.g., nonexistent, sparse,inaccurate, etc.) such that a mobile device may be unable to determineor otherwise estimate its location to a desired level of accuracy based,at least in part, on the wireless signals which may be received.Conversely, as used herein an “area of location certainty” is intendedto specify at least one region in space for which wireless signalinglocation information may be sufficiently available to allow a mobiledevice to determine or otherwise estimate its location to a desiredlevel of accuracy based, at least in part, on wireless signals which maybe received. Thus, for example, in certain instances an electronic mapand/or other like information (e.g., a radio signal heatmap, etc.) mayinclude distinct areas that may be considered as either an area oflocation certainty or an area of location uncertainty based, at least inpart, on the availability or unavailability, respectively, of adequatewireless signaling information with regard to the signaling environmentwithin a given area.

By way of one particular example, an electronic map may specify a floorplan for a building comprising an older section and a newly constructedsection. Since the older section of the building has been in place forsome time, let us assume that sufficient wireless signaling locationinformation is known and available to allow a mobile device to estimateits current location while in the older section of the building to adesired level of accuracy based, at least in part, on the wirelesssignals received therein. For example, a mobile device may have accessto a radio signal heatmap, and/or the like, which may allow the mobiledevice to estimate its location within the older section of the buildingbased on signals received from certain transmitting devices.Accordingly, an area within the older section of the building in thisexample may represent an “area of location certainty” with respect tothe present description.

However, wireless signaling location information may be lacking withregard to all or part of the newly constructed section of the building.Thus, an area within the newly constructed section of the building inthis example may represent an “area of location uncertainty” withrespect to the present description since adequate wireless signalinglocation information is not available. Therefore, a user of a mobiledevice may, for example, travel through a portion of the newlyconstructed section of the building and end up somewhere in the oldersection of the building, which may represent a transition from an areaof location uncertainty to an area of location certainty and at whichpoint a position fix (of a desired level of accuracy) may be determined(e.g., using the wireless signaling location information available forthe older section of the building). As described in greater detailherein, a mobile device may gather wireless signaling locationinformation, other movement information, etc., while in an area oflocation uncertainty and possibly provide all or part of thatinformation and/or information derived therefrom, e.g., as part of atravel log, etc., to one or more other devices along with the positionfix. Thus, for example, separately or in addition to gathering wirelesssignaling location information, a mobile device may gather inertialand/or environmental sensor data from onboard sensors while in the newlyconstructed section of the building, and such gathered movementinformation may subsequently be used for dead reckoning or other likepositioning purposes.

By way of another example, an electronic map may specify in outdoor areathat is adjacent to a structure comprising an indoor area. Here, forexample, all or part of an outdoor area may represent an “area oflocation certainty” with respect to the present description if wirelesssignals may be adequately received by a mobile device, e.g., from one ormore SPS or other like location services, to allow the mobile device todetermine or otherwise estimate its location to a desired level ofaccuracy based thereon. Accordingly, an area may be considered an areaof location certainty if known wireless signals may be adequatelyreceived by a mobile device while in such an area to allow the mobiledevice to determine otherwise estimate its location to a desired levelof accuracy based, at least in part, thereon. Assuming, that in thisexample, all or part of the structure may interfere with the mobiledevice acquiring such known wireless signals when the mobile device iswithin the structure, and further that there is an inadequate amount ofwireless signaling location information available for an area with inthe structure to allow the mobile device to estimate its location to adesired level of accuracy, then such an area within the structure mayrepresent an “area of location uncertainty” with respect to the presentdescription. However, a user of a mobile device may, for example, travelthrough a portion of such an indoor structure and end up somewhereoutside, which may represent a transition from an area of locationuncertainty to an area of location certainty since at or about thatpoint in time a position fix may be determined within the area oflocation certainty. Again as described in greater detail herein, amobile device may gather wireless signaling location information, othermovement information, etc., while in such an area of locationuncertainty and possibly provide all or part of that information and/orinformation derived therefrom, e.g., as part of a travel log, etc., toone or more other devices along with the position fix.

One or more measurements gathered over a period of time within an areaof location uncertainty by a mobile device may be considered along witha subsequently obtained position fix (e.g., an estimated location of themobile device within an area of location certainty) to detect movementsand/or position locations of the mobile device within an indoorenvironment. For example, a position fix may be obtained based on SPSsignals or other positioning system signals received by a mobile deviceupon transitioning to an area of location certainty, e.g., at somelocation position within or near to an indoor structure. For example,SPS signals may be received at or near an exit/entryway of an indoorstructure, e.g., as a mobile device is moved out of an indoor structure.As illustrated in the examples herein, by gathering various sensormeasurements prior to obtaining such a position fix, it may be possibleto estimate a trajectory and/or path of travel of the mobile device in aperiod of time leading up to the position fix while the mobile device iswithin an area of location uncertainty. Moreover, in certain exampleimplementations, various signaling characteristics may be gathered foran area of location uncertainty which may permit various signalingenvironment characteristic models and/or like radio heatmaps to beestablished, maintained, refined, and which may at some point in timeallow for location position determination by mobile devices within anindoor structure (e.g., an area of location uncertainty may become anarea of location certainty once an adequate amount of wireless signalinglocation information is available).

By way of example, certain measurements may be obtained with a mobiledevice and used to determine movements of the mobile device during aperiod of time, e.g., while the mobile device may be within an area oflocation uncertainty within an indoor structure and possibly leading upto a position fix. Such measurements may, for example, comprise sensormeasurements from one or more inertial sensors in the mobile device,signal measurements from one or more wireless signals received by aradio in the mobile device, environment measurements from one or moreenvironmental sensors in the mobile device, input measurements receivedfrom one or more user input mechanisms in the mobile device, and/or thelike or some combination thereof, and which may be time-stamped orotherwise temporally relatable in some manner.

In certain example implementations, a mobile device may process all orpart of the gathered measurements and/or the position fix in some mannerto estimate its previous movements and/or location positions, andpossibly to further characterize all or part of an indoor structure. Incertain implementations, a mobile device may simply act to gathermeasurements and obtain a position fix and report such to an externaldevice for further processing. In certain implementations, a mobiledevice may perform certain further processing on its own, e.g., usingsuch gathered travel history.

In certain example implementations, a mobile device may determinewhether all or part of its gathered travel history with regard to one ormore areas of location uncertainty is to be reported, e.g., transmittedvia one or more messages and/or encoded data files to one or moreexternal computing devices. Such a determination may, for example, bebased, at least in part, on a number and/or type of measurementsobtained, a period time associated with the obtained measurements and/ora position fix, the particular indoor structure and/or other potentialareas of location uncertainty, a received message, one or more flaggedor otherwise identified values (flag value), one or more thresholdvalues being satisfied, and/or the like or some combination thereof. Inresponse to a determination that a travel history is to be reported, amobile device may, for example, establish and transmit a travel logbased, at least in part, on at least a portion of the gathered travelhistory (e.g., measurements from within an area of location uncertaintyand position fix from within an area of location certainty).

In certain example implementations, a mobile device may performadditional processing to determine an estimated trajectory within anarea of location uncertainty leading to a position fix within an area oflocation certainty based, at least in part, on the gathered travelhistory, e.g., using reversed dead reckoning and/or other liketechniques. In certain example implementations, a mobile device mayperform additional processing to estimate its path of travel with regardto an area of location uncertainty within an indoor structure based, atleast in part, on an estimated trajectory, e.g., using an electronic mapand/or a routability graph for the indoor structure, etc.

In certain example implementations, a mobile device may performadditional processing to characterize all or part of an environment atone or more points along its estimated trajectory within an area oflocation uncertainty, e.g., based, at least in part, on signalmeasurements/characteristics for wireless signals received from varioustransmitting devices. For example, a characterized environment may beindicative of at least a portion of a received signal heatmap, radiomodel, and/or the like for an indoor structure or portion thereof.

As such, a mobile device may, for example, establish and transmit atravel log for at least a portion of an area of location uncertaintythat may comprise all or part of, and/or may be based at least in parton, a gathered travel history, one or more measurements, one or moreposition fixes from an area of location certainty, one or more estimatedtrajectories, one or more estimated paths of travel, one or morecharacterized environments, and/or the like or some combination thereof.

In certain example implementations, an external computing device mayobtain one or more travel logs or portions thereof from one or moremobile devices for one or more areas of location uncertainty.

In certain example implementations, an external computing device mayprocess at least a portion of the reported measurements and a positionfix received from a mobile device in a travel log in some manner todetect the mobile device's movements and/or position locations, and/orto further characterize all or part of an area of location uncertaintywith regard to it signaling environment. For example, an externalcomputing device may determine an estimated trajectory of a mobiledevice within an area of location uncertainty leading to a position fixwithin an area of location certainty based, at least in part, on areceived travel log, e.g., using reversed dead reckoning and/or otherlike techniques. For example, an external computing device may estimatea mobile device's path of travel with regard to an area of locationuncertainty based, at least in part, on an estimated trajectory, e.g.,using an electronic map and/or a routability graph for an applicableindoor structure, etc. For example, an external computing device maycharacterize an environment at one or more position locations along amobile device's estimated trajectory and/or one or more positionlocations of an electronic map or the like, e.g., based, at least inpart, on signal measurements for wireless signal received fromtransmitting devices by the mobile device while located within an areaof location uncertainty. For example, a characterized environment may beindicative of at least a portion of a signal heatmap and/or the like foran indoor structure or portion thereof. In certain exampleimplementations, an external computing device may establish/maintain asignal heatmap and/or the like for an indoor structure or portionthereof based on travel logs obtained from a plurality of mobile devicesover time, e.g., as part of a crowd-sourcing server capability. Thus,for example, an indoor structure that may initially be considered anarea of location uncertainty may subsequently be considered an area oflocation certainty.

In certain example implementations, an external computing device (e.g.,as part of a crowd-sourcing server capability) may provide a suggestedroute of travel associated with an area of location uncertainty to amobile device. Hence, a mobile device may, for example, indicate such asuggested route of travel to a user with regard to an indoor structure,which, if taken, may permit further measurements to be gathered along atleast a portion of the suggested route of travel within an area oflocation uncertainty. As such, over time, an example crowd-sourcingserver capability may establish/maintain various beneficial navigationdata that may be of use by mobile devices in performing navigationand/or positioning functions relative to an indoor structure, etc.

As used herein the term “indoor structure” may, for example, apply to(all or part of) one or more natural and/or man-made physicalarrangements of object(s), the knowledge of which may be of use to auser of mobile device. For example, an indoor structure may comprise allor part of a building that a user of a mobile device may enter into,exit from, and/or otherwise move about within. Some example indoorstructures may comprise a mixture of indoor and outdoor spaces. Incertain instances, an indoor structure may comprise one or moredistinguishable regions. In certain instances, for example, two or moredifferent regions within an indoor structure may be distinguished fromone another based, at least in part, on various physical arrangements ofobjects, e.g., floors, ceilings, decks, walls, staircases, elevators,walkways, etc. Thus, for example, two or more regions of a structure mayrelate to two or more different levels (e.g., floors) of a building, twoor more office suites in a building, stores in a shopping mall, etc.Unless otherwise stated, for the examples herein, it will be assumedthat an indoor structure comprises one or more areas of locationuncertainty, and conversely that and outdoor area or the like comprisesat least one area of location certainty within which a mobile device mayobtain a position fix of a desired accuracy.

Attention is now drawn to FIG. 1, which is a schematic block diagramillustrating an example environment 100 that includes a mobile device102 and an external computing device 106.

As illustrated, mobile device 102 may be located at various positions154 within an indoor structure 150. By way of example, mobile device 102may comprise any electronic device that may be moved about by a userwithin a structure and which comprises a network interface 114. In thisexample implementation network interface 114 comprises a radio 132 forreceiving signals transmitted by transmitters 130 (e.g., access pointdevices, cell towers, beacon transmitters, etc.) and/or possibly otherresources in network(s) 104, etc. Thus, by way of some examples, mobiledevice 102 may comprise a cell phone, a smart phone, a computer (e.g., apersonal computer such as a laptop computer, a tablet computer, awearable computer, etc.), a navigation aid, a digital book reader, agaming device, a music and/or video player device, a camera, etc.

Apparatus 116 is representative of circuitry, such as, e.g., hardware,firmware, a combination of hardware and software, and/or a combinationof firmware and software or other like logic that may be provided inmobile device 102 for use in characterizing indoor structure 150 based,at least in part, on detected movements and/or position locations ofmobile device 102.

In certain example implementations, mobile device 102 may functionexclusively or selectively as a stand-alone device, and may provide aone or more capabilities/services of interest/use to a user. In certainexample implementations, mobile device 102 may communicate in somemanner with one or more other devices, for example, as illustrated bythe wireless communication link to the cloud labeled network(s) 104.Network(s) 104 may be representative of one or more communication and/orcomputing resources (e.g., devices and/or services) which mobile device102 may communicate with or through, e.g., via network interface 114using one or more wired or wireless communication links. Thus, incertain instances mobile device 102 may receive (or send) data and/orinstructions via network(s) 104. In certain instances, mobile device 102may, for example, not only receive a signal from a transmitter 130, butmay also transmit a signal to such a transmitter (e.g., having areceiver).

In certain example implementations, mobile device 102 may be enabled toreceive signals associated with one or more wireless communicationnetworks, location services, and/or the like or any combination thereofwhich may be associated with one or more transmitters 130 and/ornetwork(s) 104.

Mobile device 102 may, for example, be enabled (e.g., via networkinterface 114) for use with various wireless communication networks suchas a wireless wide area network (WWAN), a wireless local area network(WLAN), a wireless personal area network (WPAN), and so on. The term“network” and “system” may be used interchangeably herein. A WWAN may bea Code Division Multiple Access (CDMA) network, a Time Division MultipleAccess (TDMA) network, a Frequency Division Multiple Access (FDMA)network, an Orthogonal Frequency Division Multiple Access (OFDMA)network, a Single-Carrier Frequency Division Multiple Access (SC-FDMA)network, and so on. A CDMA network may implement one or more radioaccess technologies (RATs) such as cdma2000, Wideband-CDMA (W-CDMA),Time Division Synchronous Code Division Multiple Access (TD-SCDMA), toname just a few radio technologies. Here, cdma2000 may includetechnologies implemented according to IS-95, IS-2000, and IS-856standards. A TDMA network may implement Global System for MobileCommunications (GSM), Digital Advanced Mobile Phone System (D-AMPS), orsome other RAT. GSM and W-CDMA are described in documents from aconsortium named “3rd Generation Partnership Project” (3GPP). Cdma2000is described in documents from a consortium named “3rd GenerationPartnership Project 2” (3GPP2). 3GPP and 3GPP2 documents are publiclyavailable. A WLAN may include an IEEE 802.11x network, and a WPAN mayinclude a Bluetooth network, an IEEE 802.15x, for example. Wirelesscommunication networks may include so-called next generationtechnologies (e.g., “4G”), such as, for example, Long Term Evolution(LTE), Advanced LTE, WiMAX, Ultra Mobile Broadband (UMB), and/or thelike.

In certain example implementations, mobile device 102 may be enabled(e.g., via an SPS receiver 140) for use with various SPS signals 162from one or more transmitting devices of one or more SPS 160, such as, aGlobal Navigation Satellite System (GNSS), or other like satelliteand/or terrestrial locating service, a location based service (e.g., viaa cellular network, a WiFi network, etc.).

As further illustrated, in certain example implementations, mobiledevice 102 may be comprise one or more inertial sensors 131, such as,one or more accelerometers, one or more gyrometers/gyroscopes, and/orthe like or some combination thereof. In certain exampleimplementations, mobile device 102 may be comprise one or moreenvironmental sensors 134, such as, one or more magnetometers and/or acompass, one or more barometers, one or more thermometers, one or morelight transducers and/or cameras, one or more sound transducers and/ormicrophones, and/or the like or some combination thereof. In certainexample implementations, mobile device 102 may be comprise one or moreuser input mechanisms 136, such as, one or more buttons, keys, and/orknobs, one or more touch screens, and/or the like or some combinationthereof. In certain example instances, a user input mechanism 136 maycomprise or use one or more environmental sensors, such as, a microphoneand/or a camera to receive user inputs.

An example computing device 106 is illustrated as being connected tonetwork(s) 104 via a network interface 118, which in certainimplementations may be similar to network interface 114. Computingdevice 106 may, for example, comprise one or more computing platforms,e.g., servers, etc., which may provide an apparatus 120. Apparatus 128is representative of circuitry, such as, e.g., hardware, firmware, acombination of hardware and software, and/or a combination of firmwareand software or other like logic that may be provided in computingdevice 106 for use in characterizing indoor structure 150 based, atleast in part, on detected movements and/or position locations of mobiledevice 102. Apparatus 120 may, for example, obtain (and/or maintain) oneor more travel logs 142 from (and/or for) one or more mobile devices.Apparatus 120 may, for example, establish and/or maintain one or moreelectronic maps 146 for one or more indoor structures. Apparatus 120may, for example, establish and/or maintain one or more routabilitygraphs 148 for one or more indoor structures. Apparatus 120 may, forexample, receive all or part of a travel log 142 from mobile device 102via networks 104. Apparatus 120 may, for example, transmit all or partof electronic map 146 and/or all or part of routability graph 148 tomobile device 102 via networks 104. Apparatus 120 may, for example,transmit all or part of a signal heatmap and/or the like relating to anindoor structure to one or more mobile devices via network(s) 104.

FIG. 2 is a schematic block diagram illustrating certain features of anexample mobile device 102 for use in characterizing an indoor structure(an area of location uncertainty) based on detected movements and/orposition locations of the mobile device, in accordance with animplementation.

As illustrated mobile device 102 may comprise one or more processingunits 202 to perform data processing (e.g., in accordance with thetechniques provided herein) coupled to memory 204 via one or moreconnections 206. Processing unit(s) 202 may, for example, be implementedin hardware or a combination of hardware and software. Processingunit(s) 202 may be representative of one or more circuits configurableto perform at least a portion of a data computing procedure or process.By way of example but not limitation, a processing unit may include oneor more processors, controllers, microprocessors, microcontrollers,application specific integrated circuits, digital signal processors,programmable logic devices, field programmable gate arrays, or the like,or any combination thereof.

Memory 204 may be representative of any data storage mechanism. Memory204 may include, for example, a primary memory 204-1 and/or a secondarymemory 204-2. Primary memory 204-1 may comprise, for example, a randomaccess memory, read only memory, etc. While illustrated in this exampleas being separate from the processing units, it should be understoodthat all or part of a primary memory may be provided within or otherwiseco-located/coupled with processing unit(s) 202, or other like circuitrywithin mobile device 102. Secondary memory 204-2 may comprise, forexample, the same or similar type of memory as primary memory and/or oneor more data storage devices or systems, such as, for example, a diskdrive, an optical disc drive, a tape drive, a solid state memory drive,etc. In certain implementations, secondary memory may be operativelyreceptive of, or otherwise configurable to couple to, computer readablemedium 260. Memory 204 and/or computer readable medium 260 may compriseinstructions 262 associated with data processing, e.g., in accordancewith the techniques and/or apparatus 116 (FIG. 1), as provided herein.

Mobile device 102 may, for example, further comprise one or more userinput mechanisms 136, one or more output devices 210, one or morenetwork interfaces 114, one or more radios 132, one or more SPSreceivers 140, one or more inertial sensors 131, and/or one or moreenvironmental sensors 134.

User input mechanisms 136 may, for example, comprise various buttons,switches, a touch pad, a trackball, a joystick, a touch screen, amicrophone, a camera, and/or the like, which may be used to receive oneor more user inputs. Output devices 210 may, for example, comprisevarious devices that may be used in producing a visual output, anaudible output, and/or a tactile output for a user.

A network interface 114 may, for example, provide connectivity to one ormore transmitters 130 and/or network(s) 104 (FIG. 1), e.g., via one ormore wired and/or wireless communication links using radio 132. SPSreceiver 216 may, for example, obtain signals from one or more SPS 160,which may be used in estimating a position fix that may be provided toor otherwise associated with one or more signals stored in memory. Forexample, SPS receiver 140 may be used to estimate a position fix thatmay indicate that mobile device 102 is at or nearby, or possiblyapproaching/leaving a particular exit/entryway of a structure.

Processing unit(s) 202 and/or instructions 262 may, for example, provideor otherwise be associated with one or more signals that may be storedin memory 204 from time to time, such as: instructions and/or encodeddata relating to apparatus 116; a plurality of measurements 220 (e.g.,time-stamped measurements, sensor measurements for inertial sensor(s),signal measurements for signal(s) received via a radio, environmentmeasurements for environmental sensor(s), input measurements for userinput mechanism(s), etc.); a period of time 222 (e.g., from a firstmeasurement timestamp to a last measurement timestamp, from a firstmeasurement timestamp to a position fix timestamp, etc.); a position fix224 (e.g., a location coordinate, a map coordinate, etc.); a travelhistory 226; a travel log 142; signal characteristics 228 (e.g., forcharacterizing a signal environment, comprising or based, at least inpart, on: received signal strength indication (RSSI) measurements, timeof flight (TOF) measurements, round-trip-time (RTT) measurements,pseudoranges, etc.); one or more pseudoranges 320 (e.g., to atransmitting device, SPS, etc.); identifiers 232 of one or moretransmitting devices (e.g., access point (AP) devices, etc.); one ormore estimated trajectories 234 (e.g., distances, velocities, headings,elevations, travel modes, etc.); one or more paths of travel 236 (e.g.,with regard to an electronic map, a routability graph, etc.); one ormore filters 238 (e.g., a Kalman filter, a particle filter, etc., foruse in estimating a trajectory and/or a path of travel, etc.); one ormore electronic maps 146 (e.g., an encoded version of all or part of afloor plan, an architectural drawing, an engineering drawing, a CADdrawing, a personnel/entity location chart, etc.); one or moreroutability graphs 148 (e.g., encoded version of navigation routesuitable for a user of a mobile device within a structure based, atleast in part, on one or more electronic maps, etc.); one or moremessages 240 (e.g., from an external computing device requesting thatcertain travel history be gathered/reported, etc.); one or more flagvalues (e.g., indicating whether to report travel history, etc.); one ormore threshold values (e.g., for use in determining whether to reporttravel history, whether to establish a travel log, associated with anumber of measurements, associated with a period time, associated with atype of at least one of the measurements, associated with a structure,etc.); and/or the like or some combination thereof.

FIG. 3 is a schematic block diagram illustrating certain features of anexample computing platform 300 for use at an external computing device106 (FIG. 1) to characterize an indoor structure (an area of locationuncertainty) he's based on detected movements and/or position locationsof one or more mobile devices, in accordance with an implementation.

As illustrated computing platform 300 may comprise one or moreprocessing units 302 to perform data processing (e.g., in accordancewith the techniques provided herein) coupled to memory 304 via one ormore connections 306. Processing unit(s) 302 may, for example, beimplemented in hardware or a combination of hardware and software.Processing unit(s) 302 may be representative of one or more circuitsconfigurable to perform at least a portion of a data computing procedureor process. By way of example but not limitation, a processing unit mayinclude one or more processors, controllers, microprocessors,microcontrollers, application specific integrated circuits, digitalsignal processors, programmable logic devices, field programmable gatearrays, or the like, or any combination thereof.

Memory 304 may be representative of any data storage mechanism. Memory304 may include, for example, a primary memory 304-1 and/or a secondarymemory 304-2. Primary memory 304-1 may comprise, for example, a randomaccess memory, read only memory, etc. While illustrated in this exampleas being separate from the processing units, it should be understoodthat all or part of a primary memory may be provided within or otherwiseco-located/coupled with processing unit(s) 302, or other like circuitrywithin computing platform 300. Secondary memory 304-2 may comprise, forexample, the same or similar type of memory as primary memory and/or oneor more data storage devices or systems, such as, for example, a diskdrive, an optical disc drive, a tape drive, a solid state memory drive,etc. In certain implementations, secondary memory may be operativelyreceptive of, or otherwise configurable to couple to, computer readablemedium 360. Memory 304 and/or computer readable medium 360 may compriseinstructions 362 associated with data processing, e.g., in accordancewith the techniques and/or apparatus 120 or apparatus 126 (FIG. 1), asprovided herein.

Computing platform 300 may, for example, further comprise one or morenetwork interfaces 118. A network interface 118 may, for example,provide connectivity to network(s) 104, mobile device 102, and/or otherdevices (FIG. 1), e.g., via one or more wired and/or wirelesscommunication links.

Processing unit(s) 302 and/or instructions 362 may, for example, provideor otherwise be associated with one or more signals that may be storedin memory 304 from time to time, such as: instructions and/or encodeddata relating to apparatus 120; one or more sets of measurements 220;one or more periods of time 222; one or more position fixes 224; one ormore travel logs 142; one or more signal characteristics 228; one ormore pseudoranges 320; one or more identifiers 232; one or moreestimated trajectories 234; one or more paths of travel 236; one or morefilters 238; one or more electronic maps 146; one or more routabilitygraphs 148; one or more suggested routes (e.g., with regard to anelectronic map and/or routability graph, structure, signalcharacterizing heatmap, etc.); and/or the like or some combinationthereof.

FIG. 4 is a flow diagram illustrating certain features of an exampleprocess or method 400 for use by a mobile device 102 for use incharacterizing an indoor structure (an area of location uncertainty)based on detected movements and/or position locations of the mobiledevice, in accordance with an implementation.

At example block 402, a mobile device may obtain a plurality ofmeasurements by gathering such measurements during a period of timewithin an area of location uncertainty. As illustrated by recursivearrow 403, in certain example implementations, block 402 may be repeatedunder certain conditions. For example, block 402 may be restarted orotherwise affected based on a threshold time value, a threshold movementvalue, a threshold power usage value, a memory limit value, and/or thelike, e.g., such that a measurement gathering effort is not open ended,overly cumbersome, wasteful, inefficient, etc. For example, if a mobiledevice is stationary within a structure (e.g., a user is sitting in achair), then block 402 may be capable of ending, restarting, timing out,waiting, being triggered, etc., at some point. For example, if a mobiledevice gathers more than or less than a threshold number ofmeasurements, and/or a period of time is too long or short based onthreshold values, then the resulting measurements may not be as usefulor reliable as desired. Hence, a resulting travel history may be moreuseful if it relates to recent detectable movements, signals, inputs,times, etc., which may allow for a trajectory and/or path of travelwithin at least a portion of an area of location uncertainty to beestimated in a temporally reversed manner from a subsequent position fixwithin an area of location certainty. Thus, in certain examples, aposition fix may indicate an end of a period of time at block 402. Inother example implementations, a timestamp or some time thereafter of alast measurement obtained prior to a time of the position fix mayrepresent an end of a period of time at block 402.

Furthermore, in certain example implementations, example block 404 maycomprise determining whether the mobile device is within an area oflocation uncertainty based, at least in part, on an absence ofsufficient wireless signaling location information to allow the mobiledevice to estimate its location to a desired level of accuracy, e.g.,based, at least in part, on one or more wireless signals received at themobile device. In certain in certain example implementations, at exampleblock 404 may comprise determining whether the mobile device is withinan area of location certainty based, at least in part, on a presence ofsufficient wireless signaling location information to allow the mobiledevice to estimate its location to a desired level of accuracy, e.g.,based, at least in part, on one or more wireless signals received at themobile device.

In certain further example implementations, at example block 404 maycomprise initiating the gathering of one or more measurements, e.g.,based, at least in part, on at least one of: a passage of time; at leastone signal generated by at least one sensor; and/or at least one userinput.

At example block 404, a position fix may be obtained at, or subsequentto, an end of the period of time based, at least in part, on one or moresignals received at the mobile device.

At example block 406 a mobile device may determine whether or not toreport a travel history for one or more areas of location uncertainty.Thus, for example, one or more threshold values may be considered todetermine whether or not to report a travel history. For example, atblock 406, a number and/or type of measurements within an area oflocation uncertainty gathered at block 402 may be considered indetermining whether or not to report a travel history. For example, atblock 406, a length of the period of time during which measurements weregathered within an area of location uncertainty at block 402 may beconsidered in determining whether or not to report a travel history. Forexample, at block 406, one or more messages 240, flag values 242, anoperating mode of the mobile device, and/or the like may be consideredin determining whether or not to report a travel history. As illustratedby arrow 407, in response to a “No” determination at block 406 method400 may, for example, return to block 402. In response to a “Yes”determination at block 406 method 400 may, for example, proceed to block408.

At example block 408, a travel log may be established with respect to atleast a portion of at least one area of location uncertainty to report atravel history based, at least in part, on the plurality of measurementsand corresponding position fixes within one or more areas of locationcertainty. In certain example instances, a travel log may comprise anencoded version of all or part of the plurality of measurements and/orposition fix. In certain example instances, a travel log may further oralternatively comprise one or more or some combination of: an estimatedtrajectory within an area of location uncertainty (e.g., as determinedat block 410), an estimated path of travel within an area of locationuncertainty (e.g., as determined at block 412), or a characterization ofa signal environment within an area of location uncertainty (e.g., asdetermined at block 414).

At example block 416, at least a portion of a travel log established atblock 408 may be transmitted to one or more external devices.

FIG. 5 is a flow diagram illustrating certain features of an exampleprocess or method 500 for a computing platform 300 for use at anexternal computing device 106 to characterize an indoor structure (anarea of location uncertainty) based on detected movements and/orposition locations of one or more mobile devices 102 therein, inaccordance with an implementation.

At example block 502 at least a portion of a travel log may be obtainedfrom a mobile device. For example, a travel log may be indicative of, orbased at least in part on: a plurality of measurements gathered by themobile device during a period of time within an area of locationuncertainty, and a position fix within an area of location certaintyobtained at, or subsequent to, an end of the period of time based, atleast in part, on one or more signals received at the mobile device. Incertain example implementations, a travel log may comprise an encodedversion of all or part of the plurality of measurements and/or positionfix. In certain example instances, a travel log may further oralternatively comprise one or more or some combination of: an estimatedtrajectory, an estimated path of travel, or a characterization of asignal environment, as determined by a mobile device with respect to anarea of location uncertainty.

At block 504, an estimated trajectory of a mobile device within anindoor structure leading to the position fix may be determined (e.g., ifneeded) based, at least in part on at least a portion of the pluralityof measurements and the position fix. In certain instances, for example,at block 506, an estimated path of travel may be determined, e.g., basedon an estimated trajectory with regard to an electronic map, aroutability graph, etc., for an indoor structure or portion thereof. Incertain instances, for example, at block 508, a signal environment maybe characterized, e.g., to establish/maintain a signal heatmap, etc.,for an indoor structure or portion thereof. In certain exampleimplementations, all or part of the determinations at block 504 may bebased one or more travel logs from one or more mobile devices. Incertain example implementations, at block 504 all or part of anestimated trajectory, estimated path of travel, signal environmentcharacterization (e.g., signal heatmap, etc.), etc., may be transmittedto one or more other devices, including one or more mobile devices.Furthermore, in certain example implementations, at block 504, anelectronic map, routability graph, etc., relating to an indoor structuremay be affected in some manner based, at least in part, on the variousmeasurements and/or determinations of methods 400 and/or 500.

As shown in the example methods 400 and 500 above, in certainimplementations all or part of the trajectory estimation, path of travelestimation, and/or signal environment characterization determinationswithin an area of location uncertainty may be preformed at a mobiledevice 102, a computing device 106, and/or some combination thereof(e.g., in a distributed manner) and results shared accordingly.

Attention is drawn next to FIG. 6, which is a diagram graphicallyillustrating certain detected movements and/or position locations 600 ofa mobile device starting from a time T1 (within an area of locationuncertainty) and leading to a position fix PF1 (within an area oflocation certainty) at or after a time T4, in accordance with animplementation. Thus, in this example, with regard to time, a period oftime is illustrated at points along a trajectory 602 as beginning attime T1, continuing through times T2 and T3, and ending at either timeT4 or at a time of position fix PF1.

As shown, there are several (sensor) measurements labeled S1 through S15gathered as the mobile device is moved along trajectory 602 within anarea of location uncertainty towards an area of location certainty. Ifthe period of time ends at time T4, then in such an example, sensormeasurements S1 through S14, but not S15 may be considered. If theperiod of time ends at a time of PF1, then in such an example, sensormeasurements S1 through S15 may be considered. The sensor measurementsrepresented by S1 through S15 may comprise or be based on variousinertial sensor measurements, environmental sensor measurements, and/oruser input measurements.

Additionally, as shown in FIG. 6, are several (radio signal)measurements labeled R1 through R5 gathered as the mobile device ismoved along trajectory 602 within an area of location uncertaintytowards an area of location certainty. In certain instances, a radiosignal measurement may be gathered at or about the same time as a sensormeasurement, e.g., see R1 and S2, R2 and S5, R3 and S7, and R5 and S13.In other instances, a radio signal measurement may be gathered at adifferent time, e.g., see R4 which is gathered between a time of S10being obtained and time T3.

As mentioned, in certain example implementations, measurements may betime-stamped and hence trajectory 602, for example, recreated withdetected movements from time T1 at S1 to PF1. For example, a filter maybe used to estimate one or more trajectories based on measurements inreverse temporal order, e.g., from PF1 to S15 to S14 to S13 and/or R5,then to S12 and S11 and possibly R4 or S10, S9, S8, S7 and/or R3, andthen to S6, S5 and/or R2, and then to S4 and S3, and possibly R1 or S2and then S1.

Reference is made next to FIG. 7, which is a diagram illustrating thattrajectory 602 may be related to a layout or floor plan 700 of a portionof a structure having a exit/entryway with a coordinates at or nearbythat of PF1. As graphically shown, trajectory 602 when aligned to floorplan 700 using PF1 may be oriented as shown by trajectory 702 in amanner that appears to be a possible match to the areas of floor plan700 which appear to be open for navigation by a user. For example, asmay be seen in FIG. 7, trajectory 702 appears to indicate that a userwith a mobile device moved though several connected hallways and exitedthe structure through an exit/entryway. Floor plan 700 may, for example,be considered in estimating a trajectory based on measurements.

With this in mind, as illustrated in a similar FIG. 8, a path of travel802 may be determined based on trajectory 702 and applying constraintsof an electronic map and/or routability graph. Hence, the resulting pathof travel 802 may be used for future and/or other navigational and/orpositional functions/purposes, and/or affecting an electronic map, aroutability graph, a signal or radio heatmap, etc.

As illustrated in the examples above, in particular implementations, alocation of a mobile device may be modeled as being placed at certainposition locations (points) along edges connecting neighboring nodes ina routability graph. Likewise, transitions from an initial position to asubsequent position may be modeled to occur along edges of such aroutability graph. In addition, a likelihood model may furthercharacterize possible transitions of a mobile device from an initialposition location to a subsequent position location over a time period.In a particular example, a particle filtering model and/or the like mayestablish a likelihood that a mobile device have a particular subsequentlocation, velocity and heading that is conditioned on an initiallocation, velocity and heading.

In certain example implementations, it may be possible to identify orestimate a particular travel mode based on certain measurements. Forexample, measurements may be compared to known signatures to identify orestimate that a mobile device is being transported in a particularmanner. For example, it may be inferred that a user is walking orpossibly running while carrying a mobile device based on inertial sensormeasurements. For example, it may be inferred that a user is riding onan escalator or elevator, or some other machine while carrying a mobiledevice based on inertial sensor and/or environmental measurements. Thus,a travel mode may be used to estimate a trajectory and/or path oftravel.

A particle filter and/or the like may, for example, incorporatemeasurements (e.g., R1-R5, or some subset thereof) obtained from signalsreceived from wireless access point (APs) and/or the like while in anindoor structure. In updating and predicting a state of a mobile device,a particle filter may also incorporate measurements (e.g., S1-S14 orS1-S15, or some subset thereof) obtained from various sensors on themobile device including sensors such as, for example, accelerometers,gyroscopes, magnetometers, cameras, microphones, buttons, just toprovide a few examples. In a particular implementation, a particlefilter may be used to estimate a past trajectory leading up to orpreceding a position fix (e.g., PF1). For example, as illustratedherein, a mobile device may maintain a travel history of measurementsobtained from RF receivers and/or various sensors by, for example,time-stamping and storing such measurements in a memory, and a travellog may be established. Subsequent to obtaining the stored measurements,a mobile device may obtain a position fix by, for example, obtaining aSPS signals upon exiting an indoor structure. In certain instances, aposition fix may be obtained using other techniques such as indoorpositioning techniques discussed above. Using the SPS position fix as afinal and known location point in a trajectory, a particle filter mayapply past time-stamped measurements to backtrack for tracing anestimated past trajectory leading up to the position fix, as illustratedherein.

An additional advantage of the techniques illustrated by the variousnon-limiting examples herein is that a signal heatmap and/or the likemay be established/maintained over time using crowd sourcing.

Another advantage of the techniques illustrated by the variousnon-limiting examples herein is that processing may be offloaded from amobile device to an external computing device.

Yet another advantage of the techniques illustrated by the variousnon-limiting examples herein is that one or more mobile devices mayefficiently map an unknown and/or changing environment. For example,measurement gathering may be triggered in response to a mobile deviceentering an unmapped indoor structure and/or other like area of locationuncertainty. For example, a mobile device may have a suggested routesent to it, which if taken may improve understanding of an indoorstructure.

Reference throughout this specification to “one example”, “an example”,“certain examples”, or “exemplary implementation” means that aparticular feature, structure, or characteristic described in connectionwith the feature and/or example may be included in at least one featureand/or example of claimed subject matter. Thus, the appearances of thephrase “in one example”, “an example”, “in certain examples” or “incertain implementations” or other like phrases in various placesthroughout this specification are not necessarily all referring to thesame feature, example, and/or limitation. Furthermore, the particularfeatures, structures, or characteristics may be combined in one or moreexamples and/or features.

The methodologies described herein may be implemented by various meansdepending upon applications according to particular features and/orexamples. For example, such methodologies may be implemented inhardware, firmware, and/or combinations thereof, along with software. Ina hardware implementation, for example, a processing unit may beimplemented within one or more application specific integrated circuits(ASICs), digital signal processors (DSPs), digital signal processingdevices (DSPDs), programmable logic devices (PLDs), field programmablegate arrays (FPGAs), processors, controllers, micro-controllers,microprocessors, electronic devices, other devices units designed toperform the functions described herein, and/or combinations thereof.

In the preceding detailed description, numerous specific details havebeen set forth to provide a thorough understanding of claimed subjectmatter. However, it will be understood by those skilled in the art thatclaimed subject matter may be practiced without these specific details.In other instances, methods and apparatuses that would be known by oneof ordinary skill have not been described in detail so as not to obscureclaimed subject matter.

Some portions of the preceding detailed description have been presentedin terms of algorithms or symbolic representations of operations onbinary digital electronic signals stored within a memory of a specificapparatus or special purpose computing device or platform. In thecontext of this particular specification, the term specific apparatus orthe like includes a general purpose computer once it is programmed toperform particular functions pursuant to instructions from programsoftware. Algorithmic descriptions or symbolic representations areexamples of techniques used by those of ordinary skill in the signalprocessing or related arts to convey the substance of their work toothers skilled in the art. An algorithm is here, and generally, isconsidered to be a self-consistent sequence of operations or similarsignal processing leading to a desired result. In this context,operations or processing involve physical manipulation of physicalquantities. Typically, although not necessarily, such quantities maytake the form of electrical or magnetic signals capable of being stored,transferred, combined, compared or otherwise manipulated as electronicsignals representing information. It has proven convenient at times,principally for reasons of common usage, to refer to such signals asbits, data, values, elements, symbols, characters, terms, numbers,numerals, information, or the like. It should be understood, however,that all of these or similar terms are to be associated with appropriatephysical quantities and are merely convenient labels. Unlessspecifically stated otherwise, as apparent from the followingdiscussion, it is appreciated that throughout this specificationdiscussions utilizing terms such as “processing,” “computing,”“calculating,” “determining”, “establishing”, “obtaining”,“identifying”, “applying,” and/or the like refer to actions or processesof a specific apparatus, such as a special purpose computer or a similarspecial purpose electronic computing device. In the context of thisspecification, therefore, a special purpose computer or a similarspecial purpose electronic computing device is capable of manipulatingor transforming signals, typically represented as physical electronic ormagnetic quantities within memories, registers, or other informationstorage devices, transmission devices, or display devices of the specialpurpose computer or similar special purpose electronic computing device.In the context of this particular patent application, the term “specificapparatus” may include a general purpose computer once it is programmedto perform particular functions pursuant to instructions from programsoftware.

The terms, “and”, “or”, and “and/or” as used herein may include avariety of meanings that also are expected to depend at least in partupon the context in which such terms are used. Typically, “or” if usedto associate a list, such as A, B or C, is intended to mean A, B, and C,here used in the inclusive sense, as well as A, B or C, here used in theexclusive sense. In addition, the term “one or more” as used herein maybe used to describe any feature, structure, or characteristic in thesingular or may be used to describe a plurality or some othercombination of features, structures or characteristics. Though, itshould be noted that this is merely an illustrative example and claimedsubject matter is not limited to this example.

While there has been illustrated and described what are presentlyconsidered to be example features, it will be understood by thoseskilled in the art that various other modifications may be made, andequivalents may be substituted, without departing from claimed subjectmatter. Additionally, many modifications may be made to adapt aparticular situation to the teachings of claimed subject matter withoutdeparting from the central concept described herein.

Therefore, it is intended that claimed subject matter not be limited tothe particular examples disclosed, but that such claimed subject mattermay also include all aspects falling within the scope of appendedclaims, and equivalents thereof.

What is claimed is:
 1. A method comprising, with a computing device:obtaining one or more signals representing at least a portion of atravel log from a mobile device, said travel log being indicative of orbased at least in part on: a plurality of measurements gathered by saidmobile device during a period of time within an area of locationuncertainty, and a position fix at or subsequent to an end of saidperiod of time based, at least in part, on one or more signals receivedat said mobile device within an area of location certainty; anddetermining an estimated trajectory of said mobile device within atleast a portion of said area of location uncertainty within an indoorstructure leading to said position fix based, at least in part on atleast a portion of said plurality of measurements and said position fix.2. The method as recited in claim 1, wherein at least a portion of saidplurality of measurements comprise time-stamped measurements that arebased, at least in part, on at least one of: one or more time-stampedsensor measurements from an inertial sensor in said mobile device; oneor more time-stamped signal measurements from a radio in said mobiledevice; one or more time-stamped environment measurements from anenvironmental sensor in said mobile device; or one or more time-stampedinput measurements from a user input mechanism in said mobile device. 3.The method as recited in claim 1, and further comprising, with saidcomputing device: estimating a path of travel of said mobile device withregard to said area of location uncertainty within said indoor structurebased, at least in part, on said estimated trajectory.
 4. The method asrecited in claim 1, wherein determining said estimated trajectory ofsaid mobile device further comprises: applying at least said portion ofsaid plurality of measurements and said position fix to a filter that isconstrained by at least one of: an electronic map for said indoorstructure; or a routability graph for said indoor structure.
 5. Themethod as recited in claim 1, further comprising: characterizing anenvironment at one or more points along said estimated trajectory ofsaid mobile device within said indoor structure leading to said positionfix based, at least in part, on at least a portion of said plurality ofmeasurements.
 6. The method as recited in claim 5, wherein at least aportion of said characterized environment is indicative of at least aportion of a received signal heatmap for at least a portion of saidindoor structure.
 7. An apparatus for use in a computing device, theapparatus comprising: means for obtaining at least a portion of a travellog from a mobile device, said travel log being indicative of or basedat least in part on: a plurality of measurements gathered by said mobiledevice during a period of time within an area of location uncertainty,and a position fix at or subsequent to an end of said period of timebased, at least in part, on one or more signals received at said mobiledevice within an area of location certainty; and means for determiningan estimated trajectory of said mobile device within at least a portionof said area of location uncertainty within an indoor structure leadingto said position fix based, at least in part on at least a portion ofsaid plurality of measurements and said position fix.
 8. The apparatusas recited in claim 7, wherein at least a portion of said plurality ofmeasurements comprise time-stamped measurements that are based, at leastin part, on at least one of: one or more time-stamped sensormeasurements from an inertial sensor in said mobile device; one or moretime-stamped signal measurements from a radio in said mobile device; oneor more time-stamped environment measurements from an environmentalsensor in said mobile device; or one or more time-stamped inputmeasurements from a user input mechanism in said mobile device.
 9. Theapparatus as recited in claim 7, and further comprising: means forestimating a path of travel of said mobile device with regard to saidarea of location uncertainty within said indoor structure based, atleast in part, on said estimated trajectory.
 10. The apparatus asrecited in claim 7, and further comprising: means for characterizing anenvironment at one or more points along said estimated trajectory ofsaid mobile device within said indoor structure leading to said positionfix based, at least in part, on at least a portion of said plurality ofmeasurements.
 11. A computing device comprising: a network interface;and a processing unit to: obtain, via said network interface, at least aportion of a travel log from a mobile device, said travel log beingindicative of or based at least in part on: a plurality of measurementsgathered by said mobile device during a period of time within an area oflocation uncertainty, and a position fix at or subsequent to an end ofsaid period of time based, at least in part, on one or more signalsreceived at said mobile device within an area of location certainty; anddetermine an estimated trajectory of said mobile device within at leasta portion of said area of location uncertainty within an indoorstructure leading to said position fix based, at least in part on atleast a portion of said plurality of measurements and said position fix.12. The computing device as recited in claim 11, wherein at least aportion of said plurality of measurements comprise time-stampedmeasurements that are based, at least in part, on at least one of: oneor more time-stamped sensor measurements from an inertial sensor in saidmobile device; one or more time-stamped signal measurements from a radioin said mobile device; one or more time-stamped environment measurementsfrom an environmental sensor in said mobile device; or one or moretime-stamped input measurements from a user input mechanism in saidmobile device.
 13. The computing device as recited in claim 11, saidprocessing unit to further: estimate a path of travel of said mobiledevice with regard to said area of location uncertainty within saidindoor structure based, at least in part, on said estimated trajectory.14. The computing device as recited in claim 11, wherein to determinesaid estimated trajectory of said mobile device said processing unit tofurther: apply at least said portion of said plurality of measurementsand said position fix to a filter that is constrained by at least oneof: an electronic map for said indoor structure; or a routability graphfor said indoor structure.
 15. The computing device as recited in claim11, said processing unit to further: characterize an environment at oneor more points along said estimated trajectory of said mobile devicewithin said indoor structure leading to said position fix based, atleast in part, on at least a portion of said plurality of measurements.16. The computing device as recited in claim 15, wherein at least aportion of said characterized environment is indicative of at least aportion of a received signal heatmap for at least a portion of saidindoor structure.
 17. An article comprising: a non-transitory computerreadable medium having stored therein computer implementableinstructions that are executable by a processing unit in a computingdevice to: obtain at least a portion of a travel log from a mobiledevice, said travel log being indicative of or based at least in parton: a plurality of measurements gathered by said mobile device during aperiod of time within an area of location uncertainty, and a positionfix at or subsequent to an end of said period of time based, at least inpart, on one or more signals received at said mobile device within anarea of location certainty; and determine an estimated trajectory ofsaid mobile device within at least a portion of said area of locationuncertainty within an indoor structure leading to said position fixbased, at least in part on at least a portion of said plurality ofmeasurements and said position fix.
 18. The article as recited in claim17, wherein at least a portion of said plurality of measurementscomprise time-stamped measurements that are based, at least in part, onat least one of: one or more time-stamped sensor measurements from aninertial sensor in said mobile device; one or more time-stamped signalmeasurements from a radio in said mobile device; one or moretime-stamped environment measurements from an environmental sensor insaid mobile device; or one or more time-stamped input measurements froma user input mechanism in said mobile device.
 19. The article as recitedin claim 17, said computer implementable instructions being furtherexecutable by said processing unit to: estimate a path of travel of saidmobile device with regard to said area of location uncertainty withinsaid indoor structure based, at least in part, on said estimatedtrajectory.
 20. The article as recited in claim 17, said computerimplementable instructions being further executable by said processingunit to: characterize an environment at one or more points along saidestimated trajectory of said mobile device within said indoor structureleading to said position fix based, at least in part, on at least aportion of said plurality of measurements.